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Hashicorp Vault and Elasticsearch Integration

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This is not the recommended configuration for real-time query at scale. For query and compression optimization, high-speed ingest, and high availability, you may want to consider <a href="/integrations/vault-influxdb/">Hashicorp Vault and InfluxDB</a>.

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Input and output integration overview

<p>The Hashicorp Vault plugin for Telegraf allows for the collection of metrics from Hashicorp Vault services, facilitating monitoring and operational insights.</p>

<p>The Telegraf Elasticsearch Plugin seamlessly sends metrics to an Elasticsearch server. The plugin handles template creation and dynamic index management, and supports various Elasticsearch-specific features to ensure data is formatted correctly for storage and retrieval.</p>

Integration details

Hashicorp Vault

<p>The Hashicorp Vault plugin is designed to collect metrics from Vault agents running within a cluster. It enables Telegraf, an agent for collecting and reporting metrics, to interface with the Vault services, typically listening on a local address such as <code>http://127.0.0.1:8200</code>. This plugin requires a valid token for authorization, ensuring secure access to the Vault API. Users must configure either a token directly or provide a path to a token file, enhancing flexibility in authentication methods. Proper configuration of the timeout and optional TLS settings further relates to the security and responsiveness of the metrics collection process. As Vault is a critical tool in managing secrets and protecting sensitive data, monitoring its performance and health through this plugin is essential for maintaining operational security and efficiency.</p>

Elasticsearch

<p>This plugin writes metrics to Elasticsearch, a distributed, RESTful search and analytics engine capable of storing large amounts of data in near real-time. It is designed to handle Elasticsearch versions 5.x through 7.x and utilizes its dynamic template features to manage data type mapping properly. The plugin supports advanced features such as template management, dynamic index naming, and integration with OpenSearch. It also allows configurations for authentication and health monitoring of the Elasticsearch nodes.</p>

Configuration

Hashicorp Vault

<pre><code class="language-toml">[[inputs.vault]] ## URL for the Vault agent # url = "http://127.0.0.1:8200" ## Use Vault token for authorization. ## Vault token configuration is mandatory. ## If both are empty or both are set, an error is thrown. # token_file = "/path/to/auth/token" ## OR token = "s.CDDrgg5zPv5ssI0Z2P4qxJj2" ## Set response_timeout (default 5 seconds) # response_timeout = "5s" ## Optional TLS Config # tls_ca = /path/to/cafile # tls_cert = /path/to/certfile # tls_key = /path/to/keyfile </code></pre>

Elasticsearch

<pre><code class="language-toml"> [[outputs.elasticsearch]] ## The full HTTP endpoint URL for your Elasticsearch instance ## Multiple urls can be specified as part of the same cluster, ## this means that only ONE of the urls will be written to each interval urls = [ "http://node1.es.example.com:9200" ] # required. ## Elasticsearch client timeout, defaults to "5s" if not set. timeout = "5s" ## Set to true to ask Elasticsearch a list of all cluster nodes, ## thus it is not necessary to list all nodes in the urls config option enable_sniffer = false ## Set to true to enable gzip compression enable_gzip = false ## Set the interval to check if the Elasticsearch nodes are available ## Setting to "0s" will disable the health check (not recommended in production) health_check_interval = "10s" ## Set the timeout for periodic health checks. # health_check_timeout = "1s" ## HTTP basic authentication details. ## HTTP basic authentication details # username = "telegraf" # password = "mypassword" ## HTTP bearer token authentication details # auth_bearer_token = "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9" ## Index Config ## The target index for metrics (Elasticsearch will create if it not exists). ## You can use the date specifiers below to create indexes per time frame. ## The metric timestamp will be used to decide the destination index name # %Y - year (2016) # %y - last two digits of year (00..99) # %m - month (01..12) # %d - day of month (e.g., 01) # %H - hour (00..23) # %V - week of the year (ISO week) (01..53) ## Additionally, you can specify a tag name using the notation {{tag_name}} ## which will be used as part of the index name. If the tag does not exist, ## the default tag value will be used. # index_name = "telegraf-{{host}}-%Y.%m.%d" # default_tag_value = "none" index_name = "telegraf-%Y.%m.%d" # required. ## Optional Index Config ## Set to true if Telegraf should use the "create" OpType while indexing # use_optype_create = false ## Optional TLS Config # tls_ca = "/etc/telegraf/ca.pem" # tls_cert = "/etc/telegraf/cert.pem" # tls_key = "/etc/telegraf/key.pem" ## Use TLS but skip chain &amp; host verification # insecure_skip_verify = false ## Template Config ## Set to true if you want telegraf to manage its index template. ## If enabled it will create a recommended index template for telegraf indexes manage_template = true ## The template name used for telegraf indexes template_name = "telegraf" ## Set to true if you want telegraf to overwrite an existing template overwrite_template = false ## If set to true a unique ID hash will be sent as sha256(concat(timestamp,measurement,series-hash)) string ## it will enable data resend and update metric points avoiding duplicated metrics with different id's force_document_id = false ## Specifies the handling of NaN and Inf values. ## This option can have the following values: ## none -- do not modify field-values (default); will produce an error if NaNs or infs are encountered ## drop -- drop fields containing NaNs or infs ## replace -- replace with the value in "float_replacement_value" (default: 0.0) ## NaNs and inf will be replaced with the given number, -inf with the negative of that number # float_handling = "none" # float_replacement_value = 0.0 ## Pipeline Config ## To use a ingest pipeline, set this to the name of the pipeline you want to use. # use_pipeline = "my_pipeline" ## Additionally, you can specify a tag name using the notation {{tag_name}} ## which will be used as part of the pipeline name. If the tag does not exist, ## the default pipeline will be used as the pipeline. If no default pipeline is set, ## no pipeline is used for the metric. # use_pipeline = "{{es_pipeline}}" # default_pipeline = "my_pipeline" # # Custom HTTP headers # To pass custom HTTP headers please define it in a given below section # [outputs.elasticsearch.headers] # "X-Custom-Header" = "custom-value" ## Template Index Settings ## Overrides the template settings.index section with any provided options. ## Defaults provided here in the config # template_index_settings = { # refresh_interval = "10s", # mapping.total_fields.limit = 5000, # auto_expand_replicas = "0-1", # codec = "best_compression" # } </code></pre>

Input and output integration examples

Hashicorp Vault

<ol> <li> <p><strong>Centralized Secret Management Monitoring</strong>: Utilize the Vault plugin to monitor multiple Vault instances across a distributed system, allowing for a unified view of secret access patterns and system health. This setup can help DevOps teams quickly identify any anomalies in secret access, providing essential insights into security postures across different environments.</p> </li> <li> <p><strong>Audit Logging Integration</strong>: Configure this plugin to feed monitoring metrics into an audit logging system, enabling organizations to have a comprehensive view of their Vault interactions. By correlating audit logs with metrics, teams can investigate issues, optimize performance, and ensure compliance with security policies more effectively.</p> </li> <li> <p><strong>Performance Benchmarking During Deployments</strong>: During application deployments that interact with Vault, use the plugin to monitor the effects of those deployments on Vault performance. This allows engineering teams to understand how changes impact secret management workflows and to proactively address performance bottlenecks, ensuring smooth deployment processes.</p> </li> <li> <p><strong>Alerting for Threshold Exceedance</strong>: Integrate this plugin with alerting mechanisms to notify administrators when metrics exceed predefined thresholds. This proactive monitoring can help teams respond swiftly to potential issues, maintaining system reliability and uptime by allowing them to take action before any serious incidents arise.</p> </li> </ol>

Elasticsearch

<ol> <li> <p><strong>Time-based Indexing</strong>: Use this plugin to store metrics in Elasticsearch to index each metric based on the time collected. For example, CPU metrics can be stored in a daily index named<code>telegraf-2023.01.01</code>, allowing easy time-based queries and retention policies.</p> </li> <li> <p><strong>Dynamic Templates Management</strong>: Utilize the template management feature to automatically create a custom template tailored to your metrics. This allows you to define how different fields are indexed and analyzed without manually configuring Elasticsearch, ensuring an optimal data structure for querying.</p> </li> <li> <p><strong>OpenSearch Compatibility</strong>: If you are using AWS OpenSearch, you can configure this plugin to work seamlessly by activating compatibility mode, ensuring your existing Elasticsearch clients remain functional and compatible with newer cluster setups.</p> </li> </ol>

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Useful Links

Documentation

Telegraf Quickstart Training

Infrastructure Monitoring with Telegraf

Powerful Performance, Limitless Scale

Collect, organize, and act on massive volumes of high-velocity data. Any data is more valuable when you think of it as time series data. with InfluxDB, the #1 time series platform built to scale with Telegraf.

See Ways to Get Started

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